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Randomized response technique: The procedure for collecting the information on sensitive issues by means of the survey, in which an element of chance is introduced as to what query a respondent has to answer. In the survey about abortion, for instance, a woman may be posed both the questions 'have you had an abortion' and 'have you never had an abortion', and is asked to respond to one or the other depending on the outcome of a randomizing device in her control. The response is now not revealing since no one except the respondent knows which question has been answered. Yet the data attained can be used to estimate the quantities of interest, here, for instance, the proportion of women who have had an abortion (π); if the probability of selecting the question 'have you had an abortion', P, is known and is not equal to 0.5. If y is the proportion of 'yes' answers to this question in a random sample of n respondents, one estimator of π can be given by the following formula This estimator is unbiased and has the variance, V
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Lorenz curve : Essentially the graphical representation of cumulative distribution of the variable, most often used for the income. If the risks of disease are not monotonically in
Non-response is the term generally used for the failure to give the relevant information being collected in the survey. Poor response can be because of the variety of causes, for
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Multilevel models are the regression models for the multilevel or clustered data where units i are nested in the clusters j, for example a cross-sectional study where students are
Zero-inflated Poisson regression is the model for count data with the excess zeros. It supposes that with probability p the only possible observation is 0 and with the probabilit
wat iz z difference b/n logistic regression and multiple regression analysis /
Genstat: The basic purpose piece of statistical software for the management and the analysis of data. The package incorporates the wide variety of data handling events and a wi
An approach of using the likelihood as the basis of estimation without the requirement to specify a parametric family for data. Empirical likelihood can be viewed as the example of
A rule for computing the number of classes to use while constructing a histogram and can be given by here n is the sample size and ^ γ is the estimate of kurtosis.
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